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Journal of Scientific Computing

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18-08-2017

Supercloseness of Primal-Dual Galerkin Approximations for Second Order Elliptic Problems

Authors: Bernardo Cockburn, Manuel A. Sánchez, Chunguang Xiong

Published in: Journal of Scientific Computing | Issue 1/2018

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Abstract

We show that two widely used Galerkin formulations for second-order elliptic problems provide approximations which are actually superclose, that is, their difference converges faster than the corresponding errors. In the framework of linear elasticity, the two formulations correspond to using either the stiffness tensor or its inverse the compliance tensor. We find sufficient conditions, for a wide class of methods (including mixed and discontinuous Galerkin methods), which guarantee a supercloseness result. For example, for the HDG\(_{k}\) method using polynomial approximations of degree \({k>0}\), we find that the difference of approximate fluxes superconverges with order \({k+2}\) and that the difference of the scalar approximations superconverges with order \({k+3}\). We provide numerical results verifying our theoretical results.

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Title: Supercloseness of Primal-Dual Galerkin Approximations for Second Order Elliptic Problems
Authors: Bernardo Cockburn
Manuel A. Sánchez
Chunguang Xiong
Publication date: 18-08-2017
Publisher: Springer US
Published in: Journal of Scientific Computing / Issue 1/2018
Print ISSN: 0885-7474
Electronic ISSN: 1573-7691
DOI: https://doi.org/10.1007/s10915-017-0538-0

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